3,347 research outputs found
Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-in Hybrid Electric Buses
We discuss a recently introduced ECO-driving concept known as SPONGE in the
context of Plug-in Hybrid Electric Buses (PHEB)'s.Examples are given to
illustrate the benefits of this approach to ECO-driving. Finally, distributed
algorithms to realise SPONGE are discussed, paying attention to the privacy
implications of the underlying optimisation problems.Comment: This paper is recently submitted to the IEEE Transactions on
Automation Science and Engineerin
Adaptive Transmission Power with Vehicle Density for Congestion Control
The Intelligent Transport Systems (ITS) employs the Vehicular Ad-hoc Networks (VANET) technology to prevent and reduce accidents on highways. VANET uses wireless communication technology that includes protocols and applications that provides safety and non-safety features for a safe and comfortable driving experience. A major problem with VANET is that the network channel utilized for the transmission of network packets for awareness becomes congested due to vehicles competing to use the channel leading to packet loss, high transmission delay and unfair resource usage. These problems would eventually lead to the periodic exchange of Basic Safety Messages not being delivered on time, thereby making VANET unreliable. Researchers have focused on numerous approaches for controlling congestion on the network channel such as adapting the rate of transmission of packets i.e. the number of packets that can be sent per second or adjusting the transmission power which is the distance a packet can travel. An approach is proposed in this thesis to adapt the transmission power, based on the vehicle density state of the network, with the aim of reducing congestion on the network channel and improving the performance of VANET. Results indicate that this can lead to improved performance in terms of reduced packet loss and inter-packet delay
Reducing congestion in obstructed highways with traffic data dissemination using adhoc vehicular networks
Vehicle-to-vehicle communications can be used effectively for intelligent transport systems (ITSs) and location-aware services. The ability to disseminate information in an ad hoc fashion allows pertinent information to propagate faster through a network. In the realm of ITS, the ability to spread warning information faster and further is of great advantage to receivers. In this paper we propose and present a message-dissemination procedure that uses vehicular wireless protocols to influence vehicular flow, reducing congestion in road networks. The computational experiments we present show how a car-following model and lane-change algorithm can be adapted to “react” to the reception of information. This model also illustrates the advantages of coupling together with vehicular flow modelling tools and network simulation tools
Power and Packet Rate Control for Vehicular Networks in Multi-Application Scenarios
Vehicular networks require vehicles to periodically transmit 1-hop broadcast
packets in order to detect other vehicles in their local neighborhood. Many
vehicular applications depend on the correct reception of these packets that
are transmitted on a common control channel. Vehicles will actually be required
to simultaneously execute multiple applications. The transmission of the
broadcast packets should hence be configured to satisfy the requirements of all
applications while controlling the channel load. This can be challenging when
vehicles simultaneously run multiple applications, and each application has
different requirements that vary with the vehicular context (e.g. speed and
density). In this context, this paper proposes and evaluates different
techniques to dynamically adapt the rate and power of 1-hop broadcast packets
per vehicle in multi-application scenarios. The proposed techniques are
designed to satisfy the requirements of multiple simultaneous applications and
reduce the channel load. The evaluation shows that the proposed techniques
significantly decrease the channel load, and can better satisfy the
requirements of multiple applications compared to existing approaches, in
particular the Message Handler specified in the SAE J2735 DSRC Message Set
Dictionary
Distributed Adaptation Techniques for Connected Vehicles
In this PhD dissertation, we propose distributed adaptation mechanisms for connected vehicles to deal with the connectivity challenges. To understand the system behavior of the solutions for connected vehicles, we first need to characterize the operational environment. Therefore, we devised a large scale fading model for various link types, including point-to-point vehicular communications and multi-hop connected vehicles. We explored two small scale fading models to define the characteristics of multi-hop connected vehicles. Taking our research into multi-hop connected vehicles one step further, we propose selective information relaying to avoid message congestion due to redundant messages received by the relay vehicle. Results show that the proposed mechanism reduces messaging load by up to 75% without sacrificing environmental awareness. Once we define the channel characteristics, we propose a distributed congestion control algorithm to solve the messaging overhead on the channels as the next research interest of this dissertation. We propose a combined transmit power and message rate adaptation for connected vehicles. The proposed algorithm increases the environmental awareness and achieves the application requirements by considering highly dynamic network characteristics. Both power and rate adaptation mechanisms are performed jointly to avoid one result affecting the other negatively. Results prove that the proposed algorithm can increase awareness by 20% while keeping the channel load and interference at almost the same level as well as improve the average message rate by 18%. As the last step of this dissertation, distributed cooperative dynamic spectrum access technique is proposed to solve the channel overhead and the limited resources issues. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this work by using a computationally efficient numerical approach. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors. An interdisciplinary approach referred to as entropy-based weighting is used for defining the neighbor credibility. Once the vehicle accesses the channel, we propose a decision mechanism for channel switching that is inspired by the optimal flower selection process employed by bumblebees foraging. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero
Internet of Vehicles and Real-Time Optimization Algorithms: Concepts for Vehicle Networking in Smart Cities
Achieving sustainable freight transport and citizens’ mobility operations in modern cities are becoming critical issues for many governments. By analyzing big data streams generated through IoT devices, city planners now have the possibility to optimize traffic and mobility patterns. IoT combined with innovative transport concepts as well as emerging mobility modes (e.g., ridesharing and carsharing) constitute a new paradigm in sustainable and optimized traffic operations in smart cities. Still, these are highly dynamic scenarios, which are also subject to a high uncertainty degree. Hence, factors such as real-time optimization and re-optimization of routes, stochastic travel times, and evolving customers’ requirements and traffic status also have to be considered. This paper discusses the main challenges associated with Internet of Vehicles (IoV) and vehicle networking scenarios, identifies the underlying optimization problems that need to be solved in real time, and proposes an approach to combine the use of IoV with parallelization approaches. To this aim, agile optimization and distributed machine learning are envisaged as the best candidate algorithms to develop efficient transport and mobility systems
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